Parallel Nested-Layer Particle Swarm Optimization for Bifurcation Parameter Detection

Nested-Layer Particle Swarm Optimization (NLPSO) has been proposed to detect bifurcation parameters in nonlinear dynamical systems. Bifurcation parameter detection by NLPSO is a simple method because it does not require precise initialization and does not require differential information from the dynamical system. NLPSO's disadvantage is its high computational complexity. We have proposed parallel NLPSO, which solves this problem using parallel computation and is implemented as a software library. The parallelization is based on optimizing the NLPSO algorithm for execution on multi-core CPUs. In this paper, we show the efficiency of Parallel NLPSO for computational time.